Beginning R

An Introduction to Statistical Programming

Häftad, Engelska, 2015

Av Larry Pace, Joshua Wiley

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Beginning R, Second Edition is a hands-on book showing howto use the R language, write and save R scripts, read in data files, and writecustom statistical functions as well as use built in functions. This book showsthe use of R in specific cases such as one-way ANOVA analysis, linear andlogistic regression, data visualization, parallel processing, bootstrapping,and more. It takes a hands-on, example-based approach incorporating bestpractices with clear explanations of the statistics being done. It has beencompletely re-written since the first edition to make use of the latestpackages and features in R version 3.R is a powerful open-source language and programmingenvironment for statistics and has become the de facto standard for doing,teaching, and learning computational statistics. R is both an object-oriented language and afunctional language that is easy to learn, easy to use, and completely free. Alarge community of dedicated R users and programmers provides an excellentsource of R code, functions, and data sets, with a constantly evolvingecosystem of packages providing new functionality for data analysis. R has alsobecome popular in commercial use at companies such as Microsoft, Google, andOracle. Your investment in learning R is sure to pay off in the long term as Rcontinues to grow into the go to language for data analysis and research.What You Will Learn:How to acquire and install RHot to import and export data and scriptsHow to analyze data and generate graphicsHow to program in R to write custom functionsHot to use R for interactive statistical explorationsHow to conduct bootstrapping and other advancedtechniques

Produktinformation

Utgivningsdatum2015-10-13
Mått178 x 254 x undefined mm
FormatHäftad
SpråkEngelska
Antal sidor327
Upplaga2
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9781484203743

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Dr. Larry Pace is a statistics author and educator, as well as a consultant. He lives in the upstate area of South Carolina in the town of Anderson. He is a professor of statistics, mathematics, psychology, management, and leadership. He has programmed in a variety of languages and scripting languages including R, Visual Basic, JavaScript, C##, PHP, APL, and in a long-ago world, Fortran IV. He writes books and tutorials on statistics, computers, and technology. He has also published many academic papers, and made dozens of presentations and lectures. He has consulted with Compaq Computers, AT&T, Xerox Corporation, the U.S. Navy, and International Paper. He has taught at Keiser University, Argosy University, Capella University, Ashford University, Anderson University (where he was the chair of the behavioral sciences department), Clemson University, Louisiana Tech University, LSU in Shreveport, the University of Tennessee, Cornell University, Rochester Institute of Technology, Rensselaer Polytechnic Institute, and the University of Georgia.

Part I. Learning the R Language 1. Getting Started 2. Dealing with Dates, Strings, and Data Frames 3. Input and Output 4. Control Structures Part II. Using R for Descriptive Statistics 5. Functional Programming 6. Probability Distributions 7. Working with Tables Part III. Using R for Inferential Statistics 8. Descriptive Statistics and Exploratory Data Analysis 9. Working with Graphics 10. Traditional Statistical Methods 11. Modern Statistical Methods 12. Analysis of Variance 13. Correlation and Regression 14. Multiple Regression 15. Logistic Regression 16. Modern Statistical Methods II Part IV. Taking R to the Next Level 17. Data Visualization Cookbook 18. High-performance Computing 19. Text Mining